2020
DOI: 10.1175/jcli-d-19-0649.1
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Corridors of Mei-Yu-Season Rainfall over Eastern China

Abstract: Successive mesoscale convective systems may develop for several days during the mei-yu season (June–July) over eastern China. They can yield excessive rainfall in a narrow latitudinal band (called a corridor), causing severe floods. The climatology of rainfall corridors and related environmental factors are examined using 20 yr of satellite rainfall and atmospheric data. A total of 93 corridors are observed over eastern China, with maximum occurrence at 27°–31°N. They typically last 2–3 days, but some persist … Show more

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Cited by 47 publications
(31 citation statements)
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“…However, the extremely enhanced Meiyu rainfall can induce severe flooding and cause great damage in East Asian countries. Therefore, the multiscale variability of Meiyu activity and its prediction has become one of the most important issues in these countries (Chen et al, 2017;Ding et al, 2020;Liu et al, 2020).…”
Section: Introductionmentioning
confidence: 99%
“…However, the extremely enhanced Meiyu rainfall can induce severe flooding and cause great damage in East Asian countries. Therefore, the multiscale variability of Meiyu activity and its prediction has become one of the most important issues in these countries (Chen et al, 2017;Ding et al, 2020;Liu et al, 2020).…”
Section: Introductionmentioning
confidence: 99%
“…In June and July, the analysis region centred on Shanghai is affected by meso‐scale convective systems associated with the passage of the Meiyu front, which results in very intense localized rainfall for short durations (e.g. Guan et al ., 2020). While the climate model can resolve the Meiyu frontal system and its passage through the region (A. Volonté, pers.…”
Section: Resultsmentioning
confidence: 99%
“…We emphasize that previous related works (e.g., Ozturk et al, 2018Ozturk et al, , 2019 have employed a different event-based similarity measure called event synchronization strength (ESS) (Quiroga et al, 2002), which is based on a similar rationale as our event coincidence rates. Recent studies have revealed that ESS can provide systematically biased estimates of the strength of event synchrony in the presence of temporally clustered events, i.e., events recorded at subsequent time steps (Hassanibesheli and Donner, 2019;Odenweller and Donner, 2020;Wolf et al, 2020). This effect needs to be corrected for either by employing a more sophisticated definition of an event or by declustering the event sequences obtained by simple thresholding prior to quantifying their mutual similarity (Boers et al, 2014a;Wolf et al, 2020).…”
Section: Event Coincidence Analysis (Eca)mentioning
confidence: 99%